What are the responsibilities and job description for the AWS Cloud Engineer (Plano) position at ExecutivePlacements.com?
Interview process: Onsite (Plano, TX)
We are looking for a highly skilled Senior AWS Data/Backend Engineer with strong expertise in C#, AWS Lambda, AWS Glue, and distributed caching technologies. The ideal candidate will excel at building and optimizing high-performance cloud-native APIs and backend services in a fully AWS-based environment. This role focuses heavily on API scalability, performance tuning, and data pipeline optimization.
We are looking for a highly skilled Senior AWS Data/Backend Engineer with strong expertise in C#, AWS Lambda, AWS Glue, and distributed caching technologies. The ideal candidate will excel at building and optimizing high-performance cloud-native APIs and backend services in a fully AWS-based environment. This role focuses heavily on API scalability, performance tuning, and data pipeline optimization.
- Key Responsibilities
- Design, develop, and optimize AWS Lambda functions in C# for low-latency, high-throughput workloads.
- Implement and manage distributed caching using Redis/ElastiCache or OpenSearch.
- Enhance and support AWS Glue ETL pipelines, data structures, and workflows.
- Architect scalable backend services using API Gateway, Lambda, S3, and Glue Catalog.
- Optimize data querying patterns across Aurora, DynamoDB, Redshift, or similar databases.
- Perform end-to-end performance profiling and bottleneck analysis across APIs and data pipelines.
- Improve observability with CloudWatch, X-Ray, and structured logging.
- Ensure all cloud solutions meet best practices for security, scalability, reliability, and cost efficiency.
- Collaborate with cross-functional teams to deliver high-performance APIs and backend systems.
- 5 years in backend engineering, cloud engineering, or data engineering.
- Strong expertise in C#/.NET with hands-on AWS Lambda experience.
- Experience implementing Redis/ElastiCache or OpenSearch caching layers.
- Hands-on with AWS Glue, Glue Catalog, ETL optimization, and data lakes.
- Strong knowledge of core AWS services: Lambda, API Gateway, S3, IAM, CloudWatch.
- Experience with cloud databases: Aurora, DynamoDB, Redshift.
- Strong understanding of data modeling, partitioning, and schema optimization.
- Excellent debugging, performance tuning, and problem-solving abilities.
- Experience with event-driven architectures (Kinesis, Kafka, SNS, SQS).
- Familiarity with CI/CD pipelines and automated deployments.
- Knowledge of AWS cost optimization practices.
- Understanding of DevOps/SRE monitoring and high-availability concepts.